What Will Automated Stores Bring To the Retail Industry In China?

摘要：
In China, the application of big data in the field of retailing is mainly contributed by the e-commerce industry. However, the offline retail industry in western countries undertook the transformation much sooner and more thorough. Cases like Walmart’s Beer+Diaper strategy etc. are the early explorations of the application of big data in the retail industry.

One day in the end of 2015, a consumer went to one of Yonghui Supermarket’s automated stores in Fuzhou. At the entrance he used his smart phone to scan the membership card. Information on detergent was then sent to his phone.

“You purchased one bag of detergent a month ago in this store. The system calculates that your detergent supply might run out soon.”

Such retail store automation solution is from an Italian provider called Datalogic. When entering the local markets in China, the company’s solution was having trouble gaining momentum. But nowadays the retail industry in China is finally embracing innovative solutions that utilize the power of data.

So, will this be a trend in the retail industry this year?

Automated stores have created a new service scene. Aside from all those fancy automation devices in the stores, the big data collected from the offline user base also matters a lot. In China, the application of big data in the field of retailing is mainly contributed by the e-commerce industry. However, before e-commerce went big in the country, international brands such as Walmart and Target have already explored the use of big data in retailing. But due to the lack of mature technologies (given the explorations took place in the PC era), the methods to collect data back then were quite inefficient.

Walmart collects data and later predicts offline consumers’ shopping pattern mainly by recording the shopping receipts. On every Friday, there’s a tendency that many adult men will go to the supermarket to buy diapers for their kids while getting themselves some beer, a shopping pattern discovered by Walmart’s staff through data collected from the receipts. But after the beer+diaper case went viral, there hasn’t been more successful cases.

Target has a different approach, which is quite complicated. First Target recorded two-month-pregnant women in offline activities, which data was later used to build analysis models. These models that Target built were quite useful. For example, after keeping track of recorded pregnant women, Target found out that many of them would tend to buy big-sized fragrance-less hand cream, and later would tend to buy nutritional supplements that contain Calcium, magnesium, iron and zinc.

Similar cases have already become popular a few years ago in China, but the retail industry didn’t seem to take them too seriously. It wasn’t until recently that the retail industry has finally started to learn the application of big data from the e-commerce industry. There are mainly three reasons for this phenomenon:

a. The demand of the market exceeded supply, allowing businesses to grow more easily even though their operation model was inefficient and unorganized.

b. Challenges brought by the rise of e-commerce forced the retail industry to rethink about their core competitiveness. After several explorations, the retail industry figured that comprehensive channels would be the future tendency of retailing and that big data would be the backbone of such model.

c. Online retailing not only shunted a proportion of consumers from offline retailing, but also has nurtured online consuming habit and built online consumer base. Compared to the challenges brought by the e-commerce industry, offline retail industry fears the change of consuming habit the most.

Besides the three reasons mentioned above, if the retail industry in China adopts the same methods that Walmart and Target use, retail businesses would not only suffer from the poor localization, but also the problems on cost. In its early stage, Walmart set up satellite antennas to collect data from its branch supermarkets while Target was pretty much using mathematic methods to analyze data. And up till 2015, several solutions for the Chinese retail industry were proposed:

1. The Wanda FFAN approach

Through installing information and Internet infrastructures such as Wi-Fi and Beacon etc., retail businesses can build a relatively user-friendly mobile commercial environment. It’s just like building an information high way, on which there are cars coming and going and application scenarios such as going inside a store to buy merchandise, shopping guidance, restaurant reservations, and movie ticket reservations etc.

FFAN also adopts a membership system that integrates major brands such as LV and Prada etc. into one membership card. Memberships from other sectors like airlines, cinemas, and restaurants etc. will be also included. In this case, consumers can manage and accumulate credits using just one card, sparing them the pain of keeping multiple cards and the inconveniency of managing too many cards.

This kind of approach is similar to Alipay and traditional banks. Traditional banks adopt a vertical account system while Alipay is horizontal. Make no mistake, simple changes of such system can bring profound transformation. Horizontal systems are better fitted for today’s information society where time, content, and consumer groups become more fragmented. Thus, breaking the information barrier and building up connections between different systems are essential.

At present, the main obstacle of carrying out membership systems similar to the one that FFAN is using is attracting more businesses and brands to join the system. Once the system works, the data it can collect will bring new commercial value. “Alibaba went into the line of e-commerce to attain data on the manufacturing industry and consumers,” Jack Ma once stated. “The same thing applies to our logistic business.” The ultimate resource that Internet can provide is after all, data.

2. Automated retail store solutions

Automated stores are very common in western societies. However, the Italian automation solution provider Datalogic was having trouble promoting automated stores in China when first entering the country.

“We found that more and more retail enterprises, especially supermarket brands, suddenly became interested in our automation solutions,” Zhang Dasheng, CEO of Datalogic China, told TMTpost.

Retail store automation solutions are a combination of smart hardware and cloud technology (hardware + data being uploaded to clouds + data analysis), pretty similar to the scenario of Yonghui supermarket in Fuzhou mentioned above.

Such systems first require the adoption of membership cards. When consumers are shopping in the automated store, they scan their membership card and get their merchandise. Everything will be completed on the handheld device, drastically reducing the cost and waiting time. As for businesses, they can monitor consumers’ shopping records and push targeted item list to them through running analysis on the data. Besides that, businesses can also manage their supply better according to the data.

Automated stores now require retail enterprises to invest money in devices in the early stage. What Datalogic does is add more value to the hardware in the aspect of data service. Meanwhile, automation also means less employees are needed, which can lower the cost for enterprises as the labor cost in China increases.

On January 2016, Datalogic announced that its sales volume in 2015 hit 530 million, among which 10% was from the Chinese market.

The CEO of Datalogic China told TMTpost that in 2015 Datalogic had an incredible surge in the filed of retailing despite the global econocmic sloth. Since 2013 Datalogic had been thinking about the issues existed in the Chinese retail industry and later came up with the efficiency issues in retail supply chain and the idea of using information technology to improve user experience. Eventually Datalogic launched its automation solutions. Datalogics’ attempts provide the Chinese retail industry with an alternative of transformation. At present, many supermarket brands are also making initiatives to become more automated. In the end, many of them became partners with Datalogic.

Now Datalogic has set up its R&d center in Shenzhen. It’s apparent that the transformation that the Chinese retail industry is undergoing will continue to bring more business opportunities.

3. Third-party payment tools go offline

Alipay and WeChat payment have been the main third-party payment tools in China. These two Internet giants are trying harder to penetrate offline scenarios with their payment products this year, allowing brick-and-motor businesses to collect data on user habit more easily.

“Each payment is a beginning, a communication,” Geng Zhijun, the general manager of WeChat Patment said. “It’s a digital start for consumers.” This small team from Tencent only has around 100 people and is trying to make offline scenarios a connector for WeChat Payment, allowing purchases to be completed in just a few seconds. However, there are a lot of obstacles to be tackled before and after achieving that.

Geng Zhijun concluded that there are three ways for traditional retail companies to enter e-commerce: Build their own platform; join an e-commerce platform; add Internet function to their offline business and build a smart retail service system. According to WeChat Payment’s data, one payment can be completed within a few seconds. The logic behind this is an account system. Payment drives users to follow some official accounts on WeChat. That being said, an official account serves just like an APP. The users that APPs acquire are the fundamental users of the enterprises.

Traditional payment process doesn’t create any relationship between the customers and the supermarkets. As for third-party payment tools, however, in each payment they can get a digital user, whose data on gender, location, personal shopping pattern will be recorded and accumulated on WeChat’s database. This allows enterprises to accumulate accounts for target marketing. “From the perspective of WeChat, we are doing basically three kinds of things: accounts, traffic, and users; service and social networking; transaction,” Geng concluded.

In 2016 the retail industry will undergo profound changes, and the three big data solutions mentioned above are the directions retail businesses will go for.

At least, in the aspect of cost, some solutions will not bring more burdens to brick-and-motor businesses. Instead, they might even get subsidy. For example, when third-party payments tool go from online to offline, they use WeChat and Alipay to give out subsidies to consumers in order to attract users to consume in their stores. Datalogic on the other hand provides companies with existing solutions that have been practiced and improved in western countries, free them from the cost of coming up a system of their own. Additionally, these solutions can also lower the labor cost.

Furthermore, the acquisition of big data is also a way for offline businesses to create more value. Profit-making opportunities like targeted commercial campaign etc. are just there waiting for businesses to make use of.